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Katrina Rose Quinn

@mightyrosequinn.bsky.social

Neuroscientist in Tübingen & mother of dragons. Interested in visual perception, decision-making & expectations.

19 Posts109 Follower154 Folgt
Katrina Rose Quinn@mightyrosequinn.bsky.social · 4w ago

Thinking about this on a 14 hour train journey back from FENS in the hopes it will make the time fly 😄

Cognition & Brain Dynamics lab@brainthemind.bsky.social · 4w ago

New paper out! 🧠🚅 When scientists leave the lab to... take the train! A successful collaboration with @groupe-sncf.com, investigating how train travelers experience duration and distance. onlinelibrary.wiley.com/doi/10.1111/... @cea.fr , @inserm.fr , @univparissaclay.bsky.social @unicog.bsky.social

Earl K. Miller@earlkmiller.bsky.social · 4w ago

In visual learning, slower changes come from adjustments in connections between neurons, while faster changes come from intrinsic plasticity. Together, these two learning processes help the brain efficiently adapt to familiar information over time. www.nature.com/articles/s41... #neuroscience

Visual learning at fast and slow timescales is driven by distinct plasticity rules in primate inferotemporal cortex - Nature Communications

We rapidly distinguish familiar from novel objects, but how the brain learns this remains unclear. Using macaque inferotemporal cortex recordings and modeling, the authors show that familiarity learni...

nature.com

Joost Haarsma@jhaarsma.bsky.social · last mo.

Nice Journal club article by @mightyrosequinn.bsky.social & @fsandhaeger.bsky.social on our MEG study into false percepts. They do a great job describing and interpreting our findings (better than we did?). www.jneurosci.org/content/46/2...

False Percepts as a Window onto Visual Processing

Many of us have had that moment—seeing a flash of motion in the periphery, only to turn and realize there was nothing there. Eerily, these “false percepts” can occur without any visual evidence whatso...

jneurosci.org

Earl K. Miller@earlkmiller.bsky.social · last mo.

Dimensionality reduction is how the brain acquires knowledge. Cool new paper from the late, great, Mark Stokes. www.nature.com/articles/s41... #neuroscience

Learning shapes neural geometry in the primate prefrontal cortex - Nature Neuroscience

Learning transforms prefrontal cortex activity from flexible, high-dimensional representations into compact, task-relevant and abstract codes, enabling efficient generalization of learned rules to new...

nature.com

Siegellab@siegellab.bsky.social · 8mo ago

🚨 🆕 Preprint 🚨 How does the brain represent natural images? Using MEG + multivariate analysis, we disentangle contributions of retinotopy, spatial frequency, shape, and texture Together, our results reveal how visual features jointly and dynamically support human object recognition. link 👇

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de Gee lab@degeelab.bsky.social · 11mo ago

🧠✨ Exciting new research alert! ✨🧠 Did you know that catecholamines can reduce choice history biases in perceptual decision-making? 🧐🔍 Paper: journals.plos.org/plosbiology/... With @donnerlab.bsky.social and @swammerdamuva.bsky.social

Catecholamines reduce choice history biases in perceptual decision making

How do catecholamines, such as like noradrenaline, influence the role of prior expectations in perceptual decision-making? This study shows that pharmacologically increasing catecholamine levels reduc...

journals.plos.org

PLOS Biology@plosbiology.org · 11mo ago

How do catecholamines like #noradrenaline influence perceptual #DecisionMaking? @degeelab.bsky.social @donnerlab.bsky.social &co show that higher #catecholamine levels reduce individual choice history biases by dampening bias in the accumulation of sensory evidence @plosbiology.org 🧪 plos.io/4mMmNNX

Experimental design and effects on peripheral arousal markers. Top left: Design was within-subject, double-blinded, randomized, and placebo-controlled (Materials and methods). Additionally, the stimulus-response mapping was counterbalanced within participants Bottom: Schematic sequence of events during the spatial contrast discrimination task (Materials and methods). Participants reported the location of the highest contrast Gabor patch (difference in contrast is high for illustration only). Top right: Heart rate and pupil size measured as the average across task blocks (Materials and methods), separately for placebo and atomoxetine sessions. Every connecting line is a participant; large data points in the middle are the group averages.
Peter Kok@peterkok.bsky.social · 10mo ago

@dotproduct.bsky.social's first first author paper is finally out in @sfnjournals.bsky.social! Her findings show that content-specific predictions fluctuate with alpha frequencies, suggesting a more specific role for alpha oscillations than we may have thought. With @jhaarsma.bsky.social. 🧠🟦 🧠🤖

Contents of visual predictions oscillate at alpha frequencies

Predictions of future events have a major impact on how we process sensory signals. However, it remains unclear how the brain keeps predictions online in anticipation of future inputs. Here, we combin...

jneurosci.org

Katharina Schmack @kathaschmack.bsky.social · 10mo ago

Really enjoyed my weekend read on 𝐚𝐜𝐭𝐢𝐯𝐞 𝐟𝐢𝐥𝐭𝐞𝐫𝐢𝐧𝐠: local recurrence amplifies natural input patterns and suppresses stray activity. This review beautifully argues that sensory cortex itself is a site of memory and prediction. Food for thought on hallucinations! #neuroskyence #neuroscience

Mark Histed@markhisted.org · 10mo ago

The brain is incredibly densely connected. Human cerebral cortex may have as many as *one trillion* connections. Most of those cortical connections are recurrent, inside each area. What do they do? New paper from me in Annual Reviews: 🧪 🧠📈 1/ www.annualreviews.org/content/jour...

Tübingen SNS 2025@snstuebingen.bsky.social · 11mo ago

📢 Deadline extended! 📢 The registration deadline for #SNS2025 has been extended to Sunday, September 28th! Register here 👉 meg.medizin.uni-tuebingen.de/sns_2025/reg... PS: Students of the GTC (Graduate Training Center for Neuroscience) in Tübingen can earn 1 CP for presenting a poster! 👀

a woman in front of a white board with the words take your time written on it

ALT: a woman in front of a white board with the words take your time written on it

media.tenor.com

Matteo Carandini@carandinilab.net · 11mo ago

The two key studies of the International Brain Laboratory @intlbrainlab.bsky.social are out today! A brain-wide map of neural activity during complex behaviour www.nature.com/articles/s41... Brain-wide representations of prior information in mouse decision-making www.nature.com/articles/s41...

A brain-wide map of neural activity during complex behaviour - Nature

The International Brain Laboratory presents a brain-wide electrophysiological map obtained from pooling data from 12 laboratories that performed the same standardized perceptual decision-making task i...

nature.com

Micah G. Allen@micahgallen.com · 11mo ago

Excellent new review by @claireocallaghan.bsky.social on how noradrenaline drives learning across multiple scales of neurobiological organization - from cells to networks www.cell.com/trends/cogni...

Noradrenaline drives learning across scales of time and neurobiological organisation

The noradrenergic system plays a diverse role in learning, from optimising learning behaviour to modulating plasticity. Work bridging across micro- and macroscale levels is revealing how noradrenaline...

cell.com

Katrina Rose Quinn@mightyrosequinn.bsky.social · 11mo ago

Not long to go now! For those of you who enjoy a more intimate conference with a chance to get to know your favourite speakers I would highly recommend this right here. Reach out if you have any questions :)

Tübingen SNS 2025@snstuebingen.bsky.social · 11mo ago

🔵Tübingen SNS 2025🔵 Registration is still open for the #SNS2025 event on 6-7 October! Join us for plenary lectures 🗣️, poster sessions📊and social events 👥 about system neuroscience!🧠 Registration at meg.medizin.uni-tuebingen.de/sns_2025

Maciek Szul@maciekszul.bsky.social · last yr.

🚨🚨🚨PREPRINT ALERT🚨🚨🚨 Neural dynamics across cortical layers are key to brain computations - but non-invasively, we’ve been limited to rough "deep vs. superficial" distinctions. What if we told you that it is possible to achieve full (TRUE!) laminar (I, II, III, IV, V, VI) precision with MEG!

Overview of the simulation strategy and analysis. a) Pial and white matter boundaries surfaces are extracted from anatomical MRI volumes. b) Intermediate equidistant surfaces are generated between the pial and white matter surfaces (labeled as superficial (S) and deep (D) respectively). c) Surfaces are downsampled together, maintaining vertex correspondence across layers. Dipole orientations are constrained using vectors linking corresponding vertices (link vectors). d) The thickness of cortical laminae varies across the cortical depth (70–72), which is evenly sampled by the equidistant source surface layers. e) Each colored line represents the model evidence (relative to the worst model, ΔF) over source layer models, for a signal simulated at a particular layer (the simulated layer is indicated by the line color). The source layer model with the maximal ΔF is indicated by “˄”. f) Result matrix summarizing ΔF across simulated source locations, with peak relative model evidence marked with “˄”. g) Error is calculated from the result matrix as the absolute distance in mm or layers from the simulated source (*) to the peak ΔF (˄). h) Bias is calculated as the relative position of a peak ΔF(˄) to a simulated source (*) in layers or mm.